This paper develops an automated traffic sign update system, AutoTS, aimed at extracting the geo-location and orientation of traffic signs. To facilitate the evaluation and comparison, we construct a traffic sign localization and orientation classification benchmark, KITTI-TS, based on the KITTI dataset.

Set up an environment for the code.

conda create -n projectname python=3.10
conda activate projectname
conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia
pip install -r requirements.txt

The images in our dataset are sourced from the KITTI dataset, and the annotations are stored in the sign_id_GT.json file. Both the images and the annotation file can be accessed via this link.

For evaluation, please download our model checkpoint from this link.

Evaluation

python orientatin_train.py --eval-only

Training Detector

python train_net.py

Training

python orientatin_train.py

If you find this project helps your research, please kindly consider citing our papers in your publications.

(Under Review)

This repository is built on Detectron2.